Managed MongoDB
Assistance-operated MongoDB for document data, catalogs, mobile backends, and flexible-schema applications
Managed MongoDB is for applications that need flexible document storage but still require disciplined production operations. Assistance provides the operating layer for MongoDB while your engineers keep product and data model ownership.
Best-fit use cases#
| Use case | Why MongoDB fits |
|---|---|
| Product catalogs and content | Flexible document model for variable attributes and evolving content structures |
| Mobile and API backends | JSON-native storage pattern that maps well to application payloads |
| Event and activity records | High write throughput and flexible indexing for semi-structured data |
| Customer profile data | Nested structures and partial updates for user-centric records |
| Modernization of self-hosted MongoDB | Improve backup, monitoring, security, and upgrade discipline without changing the data model first |
What Assistance operates#
| Area | Included managed service responsibility |
|---|---|
| Provisioning | Cluster setup, replica set or sharded topology, storage sizing, network placement, and secure defaults |
| Reliability | Replica set health, failover procedures, backup schedules, retention policy, restore process, and runbooks |
| Scaling | Capacity review, shard planning when needed, balancing oversight, index and storage growth monitoring |
| Maintenance | Version lifecycle guidance, patch planning, maintenance windows, and upgrade execution inside agreed scope |
| Security | TLS, encryption options, RBAC recommendations, network isolation, audit logging options, and credential rotation support |
| Observability | Dashboards and alerts for replica health, storage, connections, operations, index usage, and backup status |
| Support | Severity-based support, escalation path, and platform incident communication |
Flexible schema still needs ownership
Assistance operates the MongoDB platform. Your team owns document design, validation rules, index requirements introduced by application changes, and business data correctness. We can review and advise, but the product data model remains customer-owned unless scoped separately.
Ownership boundary#
| Responsibility | Assistance owns | Customer owns |
|---|---|---|
| MongoDB runtime | Install, configure, monitor, patch, back up, restore, and operate clusters | Application compatibility and client behavior |
| Collections and indexes | Operational review, index health visibility, and recommendations | Collection design, required indexes, query patterns, data validation |
| Scaling | Topology recommendations and managed scale actions | Product decisions that increase data volume, retention, or write/read behavior |
| Data protection | Implement backup and restore process | Retention rules, legal requirements, data classification, recovery acceptance |
| Access | Role model guidance, service accounts, rotation procedure | User approval, identity source, application secret handling |
Deployment options#
| Option | When to choose it |
|---|---|
| Assistance physical servers | Development, test, staging, and predictable internal document workloads |
| Customer cloud account | Production clusters that must sit near application services or inside existing account controls |
| Managed cloud service operations | Assistance operates cloud-native MongoDB-compatible or hosted MongoDB services where that is the preferred deployment path |
| Hybrid | Development on Assistance infrastructure with production in a cloud region |
Reliability and recovery model#
| Topic | Managed MongoDB approach |
|---|---|
| Availability | Replica set or sharded cluster topology selected based on production requirements |
| Backups | Automated backups with retention and point-in-time recovery targets where supported and scoped |
| Restore validation | Restore tests or evidence checks for covered production environments |
| Scaling | Capacity and shard planning based on data growth, query patterns, and retention |
| Response | Severity-based support targets; 24/7 critical response available for covered production clusters |
Onboarding#
1. Workload assessment#
We review collection sizes, document growth, query patterns, indexes, write rate, retention, backup posture, current topology, downtime tolerance, and compliance requirements.
2. Managed cluster design#
Assistance proposes replica set or sharded topology, storage sizing, backup policy, monitoring, access model, maintenance windows, and migration plan.
3. Build and migration#
We provision the cluster and support data migration through dump/restore, replication-based migration, or staged cutover depending on size and downtime tolerance.
4. Operate and tune#
After go-live, we monitor replica health, storage growth, index efficiency, backup status, and capacity. Changes are coordinated through the agreed support model.
Supported capabilities#
- MongoDB replica sets for high availability
- Sharded clusters for larger datasets and write/read scaling needs
- Index usage and query performance review
- Backup retention and restore workflows scoped by plan
- TLS, RBAC, and network isolation patterns
- Migration from self-hosted or hosted MongoDB environments
Not included by default#
- Redesigning document schema or application data model
- Rewriting application queries or ODM behavior
- Unlimited shard count, storage, or retention outside the plan
- Guaranteeing performance for unreviewed index or query changes
- Compliance certification beyond the managed infrastructure scope
Related products#
- Managed Redis — Cache hot profile, session, and computed data
- Managed OpenSearch — Add search and analytics over document data
- Managed Prometheus — Monitor service health and application metrics
- Managed Kafka — Stream events into or out of MongoDB-based systems
Getting started#
Request a MongoDB assessment. We will inspect workload shape, data growth, topology, ownership boundaries, and migration options before recommending a managed cluster design.
Request MongoDB assessment →Frequently asked questions#
Do we need sharding from day one? Not always. We review dataset size, write rate, query patterns, and growth expectations before recommending sharding. Replica sets are simpler and often enough for earlier production stages.
Can you migrate from self-hosted MongoDB? Yes. Migration approach depends on version compatibility, data volume, downtime tolerance, and whether replication-based cutover is feasible.
Who owns index design? Your team owns indexes required by application queries. Assistance monitors index health and can recommend changes, but application query behavior remains customer-owned.
Can MongoDB run on Assistance physical servers? Yes, especially for development, staging, and predictable internal workloads. Production placement depends on compliance, latency, and availability needs.
What SLA applies? Availability and response targets are defined per service tier and topology. We scope measurement, exclusions, recovery objectives, and responsibilities before production go-live.